Save costs and decrease latency while using Gemini with Vertex AI context caching
As developers build increasingly sophisticated AI applications, they often encounter scenarios where substantial amounts of contextual information — be it a lengthy document, a detailed set of system instructions, a code base — need to be repeatedly sent to the model. While this data provides models with much-needed context for their responses, it often escalates […]
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